Abstract [en]

Over the last decades the healthcare domain has seen a tremendous increase and interest in methods for making inference about patient care using large quantities of medical data. Such data is often stored in electronic health records and administrative health registries. As these data sources have grown increasingly complex, with millions of patients represented by thousands of attributes, static or time evolving, finding relevant and accurate patterns that can be used for predictive or descriptive modelling is impractical for human experts. In this paper, we concentrate our review on Swedish Administrative Health Registries (AHRs) and Electronic Health Records (EHRs) and provide an overview of recent and ongoing work in the area with focus on adverse drug events (ADEs) and heart failure.

Place, publisher, year, edition, pages

CEUR-WS.org , 2017. Vol. 1960

Series

CEUR Workshop Proceedings, E-ISSN 1613-0073 ; 1960

National Category

Computer Sciences

Research subject

Computer and Systems Sciences

Identifiers

Conference

Second Workshop on Data Science for Social Good co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Dicovery in Databases (ECML-PKDD 2017), Skopje, Macedonia, September 18, 2017